Eco-Driving Control Architecture for Platoons of Uncertain Heterogeneous Nonlinear Connected Autonomous Electric Vehicles

The improvement of energy performance for platoons of autonomous connected vehicles is one of the major challenges the road transport sector is facing with. To this aim, this work addresses and solves the energy-consumption problem for uncertain heterogeneous electric nonlinear autonomous vehicles platoon via a novel Eco-Driving Control Architecture able to optimize its energy consumption performance while ensuring the fulfillment of the optimal leader tracking trajectory. Specifically, it consists of a Nonlinear Model Predictive Control (NMPC) strategy, driving the leader motion and computing the optimal ecological trajectory to be imposed on the whole platoon, and a novel distributed exponentially-stable robust PID-like protocol, driving the follower vehicles motion for achieving a precise leader-tracking with a desired transient behavior as required for the accurate implementation of the energy-saving control. The exponential stability of the overall vehicular network is analytically proven with the Lyapunov theory and the derived robust stability conditions allow the proper tuning of the control gains on the basis of the desired decay rate. The efficiency of the proposed approach is corroborated via the high-fidelity Mixed Traffic Simulator (MiTraS) co-simulation platform under different operative scenarios and a wide uncertainty range for the vehicles parameters. Simulation results confirm how the proposed architecture ensures the eco-driving behaviour for the whole vehicles platoon.